SM Mahamudul Hasan's Projects
Python solutions to CodeForces problems
Solutions of challenges of Hackerrank Python domain
This is my machine learning course work. I have collected this dataset from kaggle. There are 303 patient records with 14 features. I applied Exploratory Data Analysis methods and nine different machine learning models to predict the heart attack disease with this accuracy: XGBoost: 95.08% AdaBoost: 93.44% MLPClassifier: 93.44% Random Forest: 91.8% Gradient Boosting: 91.8% Logistic Regression: 90.16% SVM: 90.16% KNN: 88.52% Decision Tree: 81.97%.
হাতেকলমে ন্যাচারাল ল্যাঙ্গুয়েজ প্রসেসিং (এনএলপি) - শুরুর ধারণা
This is a completely machine-learning based task. We used a dataset from kaggle with 1154 website details with 32 features. More significantly, we experimented with a considerable number of machine learningmethods on actual phishing datasets and against various criteria. We identify phishing websites using six distinct machine learningclassification methods. This research obtained a maximumachievable accuracy rate of 97.17 percent for the Random Forestrule and 94.75 percent for the Gradient Boost Classifier. The Provisioningaccuracy is 94.69 percent with the Decision Tree classifier, 92.76 percent with Logistic Regression, 60.45 percent with KNN, and 56.04 percent with SVM.
His study addresses these concerns by predicting prostate cancer using six (6) machine learningtechniques: Random Forest, SVM, KNN, Logistic Regression, Neutral Network, and the Ensemble model. We gathered data from 100 patients who were placed in ten different circumstances. The data was categorised as malignant or non-cancerous. Among the six machine learning techniques, logistic regression, neuralnetworks, and ensemble learning have the potential to reach an accuracy of 95.00 percent. Ensemble learning can detect 96.55%of true positive prostate cancer in our model. KNN has a 90%accuracy rate, whereas SVM and Random Forest have an 85%accuracy rate.
This is an international hackathon that I participated in for a contest. In this hackathon project, I created a website based on three features: an eCommerce website, a charity with donations and an information blog update for Covid 19 on a single platform. This is a PHP-based website with WordPress CMS.
This is our Java project and we created a game, basically a 2D game for this project. This game shows a standard level bucket and a ball. We protect the ball from falling into the bucket. This is an amazing game and we created it with the Java Swing framework.
StudentMarks is a Java-based small project which can correctly detect student marks with some given value. It is mainly based on JavaFX for the GUI, and I use basic Java programming for this project. Core Java programming knowledge is needed for this project.
হাতেকলমে পাইথন ডিপ লার্নিং (TensorFlow 2.x) বইয়ের ব্যবহৃত নোটবুক, লিংক: http://bit.ly/bn_dl